Quantifying Soil Phosphorus Dynamics: A Data Assimilation Approach

Abstract

The dynamics of soil phosphorus (P) control its bioavailability. Yet it remains a challenge to quantify soil P dynamics. In this work we developed a soil P dynamics (SPD) model. We then assimilated eight data sets of 426-day changes in Hedley P fractions into the SPD model, to quantify the dynamics of six major P pools in eight soil samples that are representative of a wide type of soils. The performance of our SPD model was better for labile P, secondary mineral P, and occluded P than for nonoccluded organic P (Po) and primary mineral P. All parameters describing soil P dynamics were approximately constrained by the data sets. The average turnover rates were labile P 0.040 g g -1 day-1, nonoccluded Po 0.051 g g -1 day -1 , secondary mineral P 0.023 g g -1 day -1 , primary mineral P 0.00088 g g -1 day -1 , occluded Po 0.0066 g g -1 day -1 , and occluded inorganic P 0.0065 g g -1 day -1 , in the greenhouse environment studied. Labile P was transferred on average more to nonoccluded Po (transfer coefficient of 0.42) and secondary mineral P (0.38) than to plants (0.20). Soil pH and organic C concentration were the key soil properties regulating the competition for P between plants and soil secondary minerals. The turnover rate of labile P was positively correlated with that of nonoccluded Po and secondary mineral P. The pool size of labile P was most sensitive to its turnover rate. Overall, we suggest data assimilation can contribute significantly to an improved understanding of soil P dynamics.